为代理编码CLI提供长期记忆解决方案，并促进不同代理供应商之间的切换
概览
AI编码代理的长期记忆。在任务中途退出Claude Code，在同一目录中启动OpenAI Codex，继续使用而无需重新解释架构、失败的方法或未解之谜。 你的编码代理已经有记忆功能。Claude Code 会自己记录笔记，Cursor 会记住一些内容，每个平台都在添加更多内容。所有笔记都共用同一面墙：笔记存储在同一台机器上，属于同一个代理，一旦你切换工具或队友，笔记就会从视野中消失。 AI记忆是墙的另一边。 - 二十多个线束——Claude Code、Codex、Cursor、Gemini CLI、OpenCode、Grok、Devin、Kimi、Kiro 等——为一个共享内存提供能量。在任务中途退出 Claude Code，在同一目录中打开 Codex，下一个代理会接到真正的切换：你中断的地方、失败的部分、还未完成的部分。切换在这里是一种协议，而非惯例——只输入、拥有、宣称一次。
概述（AI 翻译）
AI编码代理的长期记忆。在任务中途退出Claude代码， 在同一目录中启动 OpenAI Codex，继续使用。 重新解释架构、失败的方法或开放式 问题。
网站：aimemory.sh
为什么是ai-memory（记忆）
你的编码代理可能已经有内存功能了。Claude Code 的 自己的笔记，光标记起了一些东西，每个平台都在添加更多内容。他们 所有笔记的限制都相同：笔记存在于一台机器上，属于同一个代理， 换工具或交给队友时，他们会消失在视线中。
AI记忆消除了这些限制。
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它会在各个特工之间跟踪你。 二十多个安全带（Claude Code， Codex、Cursor、Gemini CLI、OpenCode、Grok、Devin、Kimi、Kiro等） 喂养一个共享记忆。任务中途退出Claude代码，打开同一个Codex。 目录，下一个客服接起一个交接，显示你离开的位置 关闭、失败的和仍然开放的协议。切换是一种类型化协议： 每台都有一位所有者，并且只认领一次。
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它可以承载会话，而不仅仅是摘要。 以 启动代理
ai-memory run：退出Claude代码，运行ai-memory run codex，Codex得到
本页由 AI 翻译，技术细节请以原文为准。
README
以下为原文 README 节选，完整内容请查看原文。
Long-term memory for AI coding agents. Quit Claude Code mid-task, start OpenAI Codex in the same directory, continue without re-explaining the architecture, the failed approaches, or the open questions.
Website: aimemory.sh
Why ai-memory
Your coding agent probably has a memory feature already. Claude Code takes its own notes, Cursor remembers some things, and every platform is adding more. They all have the same limits: the notes live on one machine, belong to one agent, and drop out of view when you switch tools or hand the work to a teammate.
ai-memory removes those limits.
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It follows you across agents. More than twenty harnesses (Claude Code, Codex, Cursor, Gemini CLI, OpenCode, Grok, Devin, Kimi, Kiro, and others) feed one shared memory. Quit Claude Code mid-task, open Codex in the same directory, and the next agent picks up a handoff that says where you left off, what failed, and what is still open. Handoffs are a typed protocol: each one has an owner and is claimed exactly once.
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It can carry the session, not just a summary. Start agents with
ai-memory run: quit Claude Code, runai-memory run codex, and Codex gets the shared workstream plus a private, temporary local projection of Claude’s visible native history for exact details the bounded startup packet omitted. The remote server receives only the harness and session identity, never the local transcript path or body. Direct harness launches behave exactly as before. -
It follows you across projects. A small profile of how you usually work (your package manager, test layout, architecture habits) reaches every new repository at session start, so you stop re-explaining yourself. It sits below each repository’s rules file as a default. It is on by default for a single user, and on a shared server it is opt-in and private per person. See
docs/cross-project-profile.md. -
It follows you across machines. Memory lives in a server you run, on the same laptop, a homelab box, or anywhere else, so the project you left on the desktop is the project you resume on the laptop, with the same knowledge and the same open questions.
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It works for a team. Point everyone at one server, and what one person’s sessions learn, everyone’s agents can retrieve. Knowledge is
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安装
npx skillfish add akitaonrails/ai-memory